1. Filed of the invention:
The present invention relates to an object recognition method and a system used together with an industrial robot, of the type wherein the center position of an object with a cylindrical or similar profile carried on a support table is optically detected to enable the robot to reliably grip the object prior to a subsequent transfer operation.
2. Discussion of the Prior Art:
Heretofore, a system has been known wherein a charge coupled device image sensor (hereafter referred to as "CCD image sensor") catches an object to input image data therefor and wherein the gray level of the input image is binarized on the basis of a predetermined threshold value for recognizing the object based on the binarized image data. Another system has also been known which recognizes an object by directly collating the multilevel gray image for an object to be recognized with the multilevel gray image for a model object.
Where the external surface of the object is flat relative to the image sensor, in other words, where the object has a fixed reflection rate larger than the background, then the variation in the image gray level is large at the boundary of the object with the background while the variation in the image gray level within an area occupied by the object is little. Thus, the whole image of the object can be easily extracted by effecting a binarization processing of the image.
However, where an object to be recognized is cylindrical or is similar to a cylindrical shape, the image gray level moderately varies as the scanning of the image moves from the background to the object, and also within an area occupied by the object, the image gray level gradually varies as a curve function with regard to the scanning positions of the object. Thus, in the prior art method wherein such simple binarization processing of the image is carried out, it is difficult to reliably recognize the object and to precisely detect the location thereof.
Moreover, where two objects of the same cylindrical shape lie contacted in parallel relation, the variation in the image gray level is little at the boundary between the two objects. Thus, in this case, the reliable recognition of each object is difficult as well, even utilizing the prior art method involving such simple binarization processing.
In addition, the prior art object recognition method which takes the correlation in gray level between the images of an actual object and a model object in recognizing the actual object gives rise to problems in that too much information on the object to be processed is required, thereby resulting in an elongation of the processing time.